The purpose of the SNaPP Lab Boot Camp is to expose new lab members to the kinds of research we do, as well as train them with the basic techniques they’ll need to successfully design and execute their own individual and group research projects. Students receive two credits of GOVT 394 credit each semester for completing all the requirements of the boot camp. There are approximately six sessions of boot camp each semester; each session involves 1-2 hours of face-to-face meeting time and 4-6 hours of independent work, on average.
The purpose of these introductory sessions is to teach you the best practices in how and where to find research materials related to the work we do in the lab, as well as how to critically read and summarize what you find. By the end of this unit, you should be confident in your abilities to 1) find high quality research (published and posted online), 2) read that research with a more critical eye toward what scholars say they’ve demonstrated versus what they actually do, and 3) synthesize literature on research topic to assess the “conversation” that scholars have with one another through their work. Many of the papers you write for class may ask you simply to summarize and analyze articles you read. The key distinction in a literature review is that you are identifying a hole in the existing scholarship that you persuasively argue you can address with your own research. In other words, you are trying to identify and address the missing piece in our understanding of your research topic.
End Product: In addition to several smaller assignments and handouts, at the end of this unit you will produce an abbreviated literature review about the work of one particular scholar or one particular method in the field.
During the second part of boot camp, we’ll think about the foundations of research design, discussing questions like:
- What makes for a good research question?
- How do I apply existing research theories to my ideas?
- How do you design research with falsifiable hypotheses?
- What does it mean to “operationalize” your variables?
- How can we be confident that we are assessing causality and not just studying correlational patterns in the world?
- What defines an experiment and how do you design one?
End Product: In addition to several smaller assignments and handouts, at the end of this unit you will produce a proto research design document, where you propose a feasible study to collect data related to a puzzle that interests you.
The Tools of the Trade
In the third unit of Boot Camp, we focus on equipping you to analyze quantitative data. Social scientists are increasingly using a free software program called R to analyze and visualize data. Over winter break, you will work through the SSRMC’s R Module, which introduces you to the software and some basic techniques. You will also complete an assignment to help you apply what you’ve learned to an actual dataset. In the early part of the spring semester, Prof. Settle will work with you to improve and extend your skills in R so that you are able to analyze data that you’ve collected or that has been collected by other members of the lab.
End Product: At the beginning of the spring semester, you will turn in a data report including your R code and analysis from a dataset assigned to you. Over the course of the semester, you will either continue to refine and extend your analysis of that dataset, or apply what you’ve learned to a dataset of your choosing, in order to complete a polished, thorough report.
Writing an academic manuscript requires skills beyond what you’ve likely been taught before. In this unit, we will focus on the best practices for structuring an article that reports the findings of original research. The skills you’ve learned so far will help you write the front half of a paper; here, we will focus on the presentation and interpretation of your results and effective strategies for framing your paper to have maximum impact.
End Product: In addition to several smaller assignments and handouts, at the end of this unit you will build on your data report by adding the methods, results, discussion, and conclusion sections based on the analysis you’ve conducted.